title: “pHeatMap” author: “Lalit K. Gautam” date: “2022-11-27” output: pdf_document: default html_document: default —
knitr::opts_chunk$set(fig.width = 6, fig.height = 240)
library(pheatmap)
## Warning: package 'pheatmap' was built under R version 4.2.2
library(grid)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.2.3
library(matrixStats)
## Warning: package 'matrixStats' was built under R version 4.2.2
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.2.3
## Warning: package 'tibble' was built under R version 4.2.3
## Warning: package 'tidyr' was built under R version 4.2.3
## Warning: package 'readr' was built under R version 4.2.3
## Warning: package 'purrr' was built under R version 4.2.2
## Warning: package 'dplyr' was built under R version 4.2.3
## Warning: package 'stringr' was built under R version 4.2.2
## Warning: package 'forcats' was built under R version 4.2.3
## Warning: package 'lubridate' was built under R version 4.2.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.1 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ lubridate 1.9.2 ✔ tibble 3.2.1
## ✔ purrr 1.0.1 ✔ tidyr 1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::count() masks matrixStats::count()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
data <-read.csv('Data_sig_only.csv')
dim(data)
## [1] 1953 13
head(data)
## X MCI.E2f4VP16_1 MCI.E2f4VP16_2 MCI.E2f4VP16_3 MCI.siRbl2_1
## 1 Rp1 3.214168 3.164097 3.3507107 3.4181828
## 2 Rgs20 8.228287 8.287937 8.1896381 8.1700106
## 3 Gm39590 1.121027 1.268977 0.7873446 0.6265994
## 4 Sgk3 10.437536 10.430193 10.3588784 9.3440976
## 5 Ppp1r42 5.717107 5.702870 5.8732486 5.7084660
## 6 4930444P10Rik 4.613890 4.761809 4.5676766 4.4738731
## MCI.siRbl2_2 MCI.siRbl2_3 MCI.siCTL_1 MCI.siCTL_2 MCI.siCTL_3 Control_1
## 1 3.762037 3.142427 2.7328014 2.5999585 2.7264898 2.4624593
## 2 8.167616 8.093667 7.4095729 7.5008419 7.5011841 5.6730132
## 3 0.787183 0.784302 0.6248843 0.6261654 0.6240621 0.6337082
## 4 9.299508 9.239984 8.9458815 8.8852150 8.9976405 8.5795628
## 5 5.436173 5.604101 3.9153011 4.1932959 4.3346190 3.7252545
## 6 4.331399 4.937456 3.3262811 3.1136133 3.0988097 3.0719011
## Control_2 Control_3
## 1 2.5302994 2.4139779
## 2 5.7831867 5.3137188
## 3 0.6281471 0.6993603
## 4 8.5198598 8.5590849
## 5 3.6787813 3.6798810
## 6 3.2093496 3.1465363
data1 <- as.matrix(data[,-1])
rownames(data1) <- data[,1]
pheatmap(data1)
pheatmap(log2(data1 +1), scale = 'row')
pheatmap(log2(data1 +1), scale = 'row', row.names = TRUE)
pheatmap(log2(data1 +1), scale = 'row', row.names = TRUE, treeheight_row = 20, cutree_rows = 6)